Fuel property modeling by high-speed gas chromatography coupled with partial least squares data analysis.

Partial least squares (PLS) regression is a valuable chemometric tool for property prediction when coupled with gas chromatography (GC). Since the separation run time and stationary phase selection are crucial for effective PLS modeling, we study these GC parameters on the prediction of viscosity, density and hydrogen content for 50 aerospace fuels. Due to the diversity of compounds in the fuels (primarily alkanes, cycloalkanes, and aromatics), we explore both polar and non-polar stationary phase columns. The robustness for the PLS models was evaluated by their normalized root mean square error of cross-validation (NRMSECV). PLS models built for viscosity across 1-min, 3-min, 7-min, and 10-min time window (TW) high-speed GC separations produced nearly the same NRMSECV with the polar column data with an average (standard deviation) of 4.41 % (0.34 %) versus the non-polar column data of 4.69 % (0.15 %). In contrast, while the NRMSECV of density modeling with the polar column data varied more than the viscosity models, averaging 7.54 % (0.67 %), the non-polar column data produced a significantly higher average NRMSECV of 10.06 % (0.35 %). Similarly, for hydrogen content, the NRMSECV with the polar column data averaged 9.50 % (0.87 %), which was significantly lower than the NRMSECV with the non-polar column data averaging 12.10 % (0.88 %). We also investigated the impact of smoothing the GC data on the corresponding PLS models. By applying varying degrees of smoothing, we can effectively obtain similar chromatographic peak patterns in a shorter TW. For example, a 10-min smoothed chromatogram appears like the 1-min separation with no smoothing but resulted in nearly the same NRMSECV. Overall, the fast separation with a 1-min TW produced robust PLS models for viscosity with either stationary phase column, whereas for density and hydrogen content the polar stationary phase column produced superior PLS models, thus with proper stationary phase selection, a fast separation run time could be readily applied with optimal PLS property modeling results.

Anti-inflammatory and antioxidant activity of high concentrations of hydrogen in the lung diseases: a systematic review and meta-analysis.

As a small molecule, hydrogen is colorless, odorless and lightest. Many studies conducted that hydrogen can protect almost every organ, including the brain, heart muscle, liver, small intestine, and lungs. To verify whether high concentrations of hydrogen (HCH) has anti-inflammatory and antioxidant activities on respiratory system, we product a systematic review and meta-analysis. We investigated MEDLINE-PubMed, Cochrane Library, ScienceDirect, Wiley and SpringerLink database and selected in vivo studies related to the anti-inflammatory or antioxidant effects of HCH in the lung diseases which were published until September 2023. We firstly identified 437 studies and only 12 met the inclusion criteria. They all conducted in rodents. The results showed that HCH had a positive effect on the reduction of tumor necrosis factor alpha (TNF-α), interleukin (IL)-1ß, IL-4, IL-8, malondialdehyde (MDA), superoxide dismutase (SOD) and reactive oxygen species (ROS); but there is no effect on IL-6, we speculated that may contribute to the test results for different body fluids and at different points in time. This meta-analysis discovered the protective effects on inflammation and oxidative stress, but whether there exists more effects on reduction of inflammatory and oxidant mediators needs to be further elucidated.

Biochemical and biophysical drivers of the hydrogen isotopic composition of carbohydrates and acetogenic lipids.

The hydrogen isotopic composition (δ2H) of plant compounds is increasingly used as a hydroclimatic proxy; however, the interpretation of δ2H values is hampered by potential coeffecting biochemical and biophysical processes. Here, we studied δ2H values of water and carbohydrates in leaves and roots, and of leaf n-alkanes, in two distinct tobacco (Nicotiana sylvestris) experiments. Large differences in plant performance and biochemistry resulted from (a) soil fertilization with varying nitrogen (N) species ratios and (b) knockout-induced starch deficiency. We observed a strong 2H-enrichment in sugars and starch with a decreasing performance induced by increasing NO3-/NH4+ ratios and starch deficiency, as well as from leaves to roots. However, δ2H values of cellulose and n-alkanes were less affected. We show that relative concentrations of sugars and starch, interlinked with leaf gas exchange, shape δ2H values of carbohydrates. We thus provide insights into drivers of hydrogen isotopic composition of plant compounds and into the mechanistic modeling of plant cellulose δ2H values.

Methane gas in breath test is associated with non-alcoholic fatty liver disease.

Although the associations between a patient's body mass index (BMI) and metabolic diseases, as well as their breath test results, have been studied, the relationship between breath hydrogen/methane levels and metabolic diseases needs to be further clarified. We aimed to investigate how the composition of exhaled breath gases relates to metabolic disorders, such as diabetes mellitus, dyslipidemia, hypertension, and nonalcoholic fatty liver disease (NAFLD), and their key risk factors. An analysis was performed using the medical records, including the lactulose breath test (LBT) data of patients who visited the Ajou University Medical Center, Suwon, Republic of Korea, between January 2016 and December 2021. The patients were grouped according to four different criteria for LBT hydrogen and methane levels. Of 441 patients, 325 (72.1%) had positive results for methane only (hydrogen < 20 parts per million [ppm] and methane ⩾ 3 ppm). BMIs and NAFLD prevalence were higher in patients with only methane positivity than in patients with hydrogen and methane positivity (hydrogen ⩾ 20 ppm and methane ⩾ 3 ppm). According to a multivariate analysis, the odds ratio of only methane positivity was 2.002 (95% confidence interval [CI]: 1.244-3.221,P= 0.004) for NAFLD. Our results demonstrate that breath methane positivity is related to NAFLD and suggest that increased methane gas on the breath tests has the potential to be an easily measurable biomarker for NAFLD diagnosis.

Pt Loading of Phosphorus-Doped Carbon Nanotube Aerogels in Fuel Cell-Type Gas Sensors for Ultrasensitive H2 Detection.

A phosphorus-doped carbon nanotube (CNT) aerogel as the support material was loaded with Pt nanoparticles in fuel cell-type gas sensors for ultrasensitive H2 detection. The high surface area of the CNT scaffold is favorable to providing abundant active sites, and the high electrical conductivity facilitates the transport of carriers generated by electrochemical reactions. In addition, the CNT aerogel was doped with phosphorus (P) to further enhance the conductivity and electrochemical catalytic activity. As a result, the fuel cell-type gas sensor using the Pt/CNT aerogel doped with the optimal P content as the sensing material shows considerable performance for H2 detection at room temperature. The sensor exhibits an ultrahigh response of -921.9 µA to 15,000 ppm of H2. The sensitivity is -0.063 µA/ppm, which is 21 times higher than that of the conventional Pt/CF counterpart. The sensor also exhibits excellent repeatability and humidity resistance, as well as fast response/recovery; the response/recovery times are 31 and 4 s to 3000 ppm of H2, respectively. The modulation of the structure and catalytic properties of the support material is responsible for the improvement of the sensor performance, thus providing a feasible solution for optimizing the performance of fuel cell-type gas sensors.

Do exchangeable hydrogens affect the evaluation of partial mycoheterotrophy in orchids? Insights from δ2H analysis in bulk, α-cellulose, and cellulose nitrate samples.

To evaluate the nutritional modes of orchids associated with 'rhizoctonia' fungi, analyses of hydrogen (δ2H), carbon (δ13C), and nitrogen (δ15N) stable isotope ratios are usually adopted. However, previous studies have not fully accounted for exchangeable hydrogens, which could affect these evaluations. Here, we performed standard δ13C, δ15N, and δ2H analyses on bulk samples. Additionally, we conducted δ2H analysis on α-cellulose and cellulose nitrate samples to investigate whether the heterogeneity of exchangeable hydrogens among plant species influences the assessment of nutritional modes. The δ2H of orchids were consistently higher than those of surrounding autotrophic plants, irrespective of the three pretreatments. Although the rhizoctonia-associated orchid exhibited lower δ13C, its δ2H was higher than those of the autotrophs. Notably, among all response variables, δ15N and δ2H exhibited high abilities for discriminating the nutritional modes of rhizoctonia-associated orchids. These results indicate that a time-efficient bulk sample analysis is an effective method for evaluating plant nutritional modes, as the heterogeneity of exchangeable hydrogens does not significantly impact the estimation. Using δ15N and δ2H benefits the assessment of partial mycoheterotrophy among rhizoctonia-associated orchids.

Redispersing Ir Nanoparticles via a Carbon-Assisted Pyrolysis Process to Break the Activity-Stability Trade-Off of H2 Sensors.

Oxide semiconductor-supported metal nanoparticles often suffer from a high-temperature gas sensing process, resulting in agglomeration and coalescence, which significantly decrease their surface activity and stability. Here, we develop an in situ pyrolysis strategy to redisperse commercial Ir particles (∼15.6 nm) into monodisperse Ir species (∼5.4 nm) on ZnO supports, exhibiting excellent sintering-resistant properties and H2 sensing. We find that large-size Ir nanoparticles can undergo an unexpected splitting decomposition process and spontaneously migrate along the encapsulated carbon layer surface during high-temperature pyrolysis of ZIF-8. This resultant monodisperse status can be integrally reserved, accompanying further oxidation sintering. The final Irred/ZnO-450-based sensor exhibits outstanding stability, H2 response (10-2000 ppm), fast response/recovery capability (7/9.7 s@100 ppm), and good moisture resistance. In situ Raman and ex situ XPS further experimentally verify that highly dispersive Ir species can promote the electron transfer process during the gas sensing process. Our strategy thus provides important insights into the design of agglomeration-resistant gas sensing materials for highly effective H2 detection.

Switchable and conspicuous retroreflective sensors inspired by the wing scale of an emerald swallowtail.

Butterfly wings possess distinct micro/nanostructures that contribute to their vibrant coloration, light-trapping capabilities, and sensitivity to various stimuli. These complex features have inspired the creation of diverse devices and systems, such as sensors, photovoltaics, photocatalysis, and robotics. Specifically, the wing scales of the Emerald Swallowtail (Papilio palinurus) display iridescent, polarization-sensitive, and retroreflective colors due to their hierarchical structures. However, current technologies fail to mimic these natural designs fully, limiting their practical application in everyday life. In this study, we introduce a groundbreaking method for fabricating artificial wing scales that emulate the biological structure's functionality with a much simpler geometry. By integrating self-graded lossy media into metallic micro-concavity arrays, we achieve pronounced iridescent effects in both coaxial and non-coaxial arrangements, while preserving retroreflective properties. In particular, the simplified design allows for switchable color patterns based on the viewing angle. Demonstrating the concept, we successfully employ these conspicuous retroreflectors in hydrogen gas detection and the bi-directional/switchable recognition of patterned signals.

Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks.

This study innovates plasmonic hydrogen sensors (PHSs) by applying phase space reconstruction (PSR) and convolutional neural networks (CNNs), overcoming previous predictive and sensing limitations. Utilizing a low-cost and efficient colloidal lithography technique, palladium nanocap arrays are created and their spectral signals are transformed into images using PSR and then trained using CNNs for predicting the hydrogen level. The model achieves accurate predictions with average accuracies of 0.95 for pure hydrogen and 0.97 for mixed gases. Performance improvements observed are a reduction in response time by up to 3.7 times (average 2.1 times) across pressures, SNR increased by up to 9.3 times (average 3.9 times) across pressures, and LOD decreased from 16 Pa to an extrapolated 3 Pa, a 5.3-fold improvement. A practical application of remote hydrogen sensing without electronics in hydrogen environments is actualized and achieves a 0.98 average test accuracy. This methodology reimagines PHS capabilities, facilitating advancements in hydrogen monitoring technologies and intelligent spectrum-based sensing.

Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefore, eight machine learning models (linear regression (LR), Gaussian process regression (GPR), artificial neural network (ANN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical boosting regressor (CatBoost)) with particle swarm optimization (PSO) and a genetic algorithm (GA) optimizer were developed and evaluated for prediction of H2, CO, CO2, and CH4 gas yields from SCWG of lignocellulosic biomass. A total of 12 input features of SCWG process conditions (temperature, time, concentration, pressure) and biomass properties (C, H, N, S, VM, moisture, ash, real feed) were utilized for the prediction of gas yields using 166 data points. Among machine learning models, boosting ensemble tree models such as XGB and CatBoost demonstrated the highest power for the prediction of gas yields. PSO-optimized XGB was the best performing model for H2 yield with a test R2 of 0.84 and PSO-optimized CatBoost was best for prediction of yields of CH4, CO, and CO2, with test R2 values of 0.83, 0.94, and 0.92, respectively. The effectiveness of the PSO optimizer in improving the prediction ability of the unoptimized machine learning model was higher compared to the GA optimizer for all gas yields. Feature analysis using Shapley additive explanation (SHAP) based on best performing models showed that (21.93%) temperature, (24.85%) C, (16.93%) ash, and (29.73%) C were the most dominant features for the prediction of H2, CH4, CO, and CO2 gas yields, respectively. Even though temperature was the most dominant feature, the cumulative feature importance of biomass characteristics variables (C, H, N, S, VM, moisture, ash, real feed) as a group was higher than that of the SCWG process condition variables (temperature, time, concentration, pressure) for the prediction of all gas yields. SHAP two-way analysis confirmed the strong interactive behavior of input features on the prediction of gas yields.

Limestone water mixing process and hydrogen and oxygen stable isotope fractionation response under mining action.

North China type coalfield are gradually mining deep, and the mixing of groundwater is intensified. Hydrogen and oxygen isotopes are important elements for tracing groundwater movement. The fractionation response mechanism under mining conditions is not clear. In this paper, combined with numerical simulation, MixSIAR isotope mixing model and other methods, according to the δD, δ18O and hydrochemical information of various water bodies, the impact of coal mining on hydrogen and oxygen isotope fractionation is analyzed from multiple perspectives. The results show that summer soil water is the main source of recharge for limestone water, accounting for 30.7%-41.5%, and the Zhan River is the main source of recharge for limestone water. Before groundwater recharge, evaporation leads to the increase of δ18O in surface water by 0.31‰-5.58‰, water loss by 1.81%-28.00%, the increase of δ18O in soil water by 0.47‰-6.33‰, and water loss by 2.74%-35.80%. Compared with the coal mining layer, the degree of hydrogen and oxygen isotope drift and water-rock interaction in the coal mine stopping layer are significantly improved. The results of numerical simulation show that the pumping activity reduces the 18O concentration in the mining layer. The ion ratio is used as a new variable to eliminate the influence of water-rock interaction when calculating the mixing ratio. The results show that the limestone water is in a state of receiving external recharge, and mixing effect increases the δ18O in limestone water by 0.86‰ on average, and the δD increases by 0.72‰ on average. The research results explain the controlled process of hydrogen and oxygen isotope fractionation under mining conditions, which is of great significance to coal mine safety production.

Ultrathin Boundary-Less SnO2 Films with Surface-Activated Two-Dimensional Nanograins Enable Fast and Sensitive Hydrogen Gas Sensing.

Fast and reliable semiconductor hydrogen sensors are crucially important for the large-scale utilization of hydrogen energy. One major challenge that hinders their practical application is the elevated temperature required, arising from undesirable surface passivation and grain-boundary-dominated electron transportation in the conventional nanocrystalline sensing layers. To address this long-standing issue, in the present work, we report a class of highly reactive and boundary-less ultrathin SnO2 films, which are fabricated by the topochemical transformation of 2D SnO transferred from liquid Sn-Bi droplets. The ultrathin SnO2 films are purposely made to consist of well-crystallized quasi-2D nanograins with in-plane grain sizes going beyond 30 nm, whereby the hydroxyl adsorption and grain boundary side-effects are effectively suppressed, giving rise to an activated (101)-dominating dangling-bond surface and a surface-controlled electrical transportation with an exceptional electron mobility of 209 cm2 V-1 s-1. Our work provides a new cost-effective strategy to disruptively improve the gas reception and transduction of SnO2. The proposed chemiresistive sensors exhibit fast, sensitive, and selective hydrogen sensing performance at a much-reduced working temperature of 60 °C. The remarkable sensing performance as well as the simple and scalable fabrication process of the ultrathin SnO2 films render the thus-developed sensors attractive for long awaited practical applications in hydrogen-related industries.

The delayed senescence in harvested blueberry by hydrogen-based irrigation is functionally linked to metabolic reprogramming and antioxidant machinery.

Molecular hydrogen is beneficial for fruits quality improvement. However, the mechanism involved, especially cellular metabolic responses, has not been well established. Here, the integrated widely targeted metabolomics analysis (UPLC-MS/MS) and biochemical evidence revealed that hydrogen-based irrigation could orchestrate, either directly or indirectly, an array of physiological responses in blueberry (Vaccinium spp.) during harvesting stage, especially for the delayed senescence in harvested stage (4 °C for 12 d). The hubs to these changes are wide-ranging metabolic reprogramming and antioxidant machinery. A total of 1208 distinct annotated metabolites were identified, and the characterization of differential accumulated metabolites (DAMs) revealed that the reprogramming, particularly, involves phenolic acids and flavonoids accumulation. These changes were positively matched with the transcriptional profiles of representative genes for their synthesis during the growth stage. Together, our findings open a new window for development of hydrogen-based agriculture that increases the shelf-life of fruits in a smart and sustainable manner.

The role of hydrogen-rich water in delaying the pulp breakdown of litchi fruit during postharvest storage.

Previous studies have indicated that hydrogen-rich water (HW) treatment can delay fruit ripening and senescence. However, little is known about the HW-delaying pulp breakdown. In this study, eight physiological characteristics revealed that HW treatment delayed both pericarp browning and pulp breakdown of litchi fruit. To gain a comprehensive understanding of the changes in litchi pulp, a combination of multiple metabolomics and gene expression analyses was conducted, assessing 67 primary metabolites, 103 volatiles, 31 amino acids, and 13 crucial metabolite-related genes. Results showed that HW treatment promoted starch degradation, decelerated cell wall degradation and glycolysis, and maintained the flavor and quality of litchi fruit. Furthermore, HW treatment stimulated the production of volatile alcohols, aldehydes, ketones, olefins, and amino acids, which might play a vital role in HW-delaying pulp breakdown. This study sheds light on the mechanism by which HW delayed pulp breakdown by investigating small molecule metabolites and metabolic pathways.

Fructose malabsorption and fructan malabsorption are associated in patients with irritable bowel syndrome.

BACKGROUND: Food malabsorption and intolerance is implicated in gastrointestinal symptoms among patients with irritable bowel syndrome (IBS). Key triggers include fructose and fructan. Prior studies examined fructose and fructan malabsorption separately in IBS patients. None have concurrently assessed both within the same patient group. We aimed to investigate the association between fructose and fructan malabsorption in the same patients with IBS using hydrogen breath testing (HBT). METHODS: We retrospectively identified patients with IBS who underwent fructose and fructan HBTs and abstracted their results from the electronic medical record. Fructose and fructan HBTs were performed by administering a 25 g fructose solution or 10 g fructan solution, followed by breath hydrogen readings every 30 min for 3 h. Patients were positive for fructose or fructan malabsorption if breath hydrogen levels exceeded 20 ppm. RESULTS: Of 186 IBS patients, 71 (38.2%) were positive for fructose malabsorption and 91 (48.9%) were positive for fructan malabsorption. Of these patients, 42 (22.6%) were positive for fructose malabsorption and fructan malabsorption. Positive fructose HBT readings were significantly associated with positive fructan HBT readings (p = 0.0283). Patients positive for fructose malabsorption or fructan malabsorption had 1.951 times higher odds of testing positive for the other carbohydrate. CONCLUSIONS: Our results reveal a clinically significant association between fructose malabsorption and fructan malabsorption in patients with IBS. Fructan malabsorption should be assessed in patients with fructose malabsorption, and vice versa. Further studies are required to identify the mechanisms underlying our findings.

Incorporation of hydrogen-producing magnesium into minced beef meat protects the quality attributes and safety of the product during cold storage.

The impact of hydrogen (H2) producing magnesium (Mg) incorporation into minced beef meat (MBM) on the quality and safety of the product was investigated. The H2-producing Mg (H2-P-Mg)-incorporated MBMs were vacuumed (VP) and stored at 4 °C for 12 days. Other MBMs were vacuumed and gassed with H2 or N2. At the end of storage, the lowest browning index values were for H2 and H2-P-Mg samples. H2- PMg and VP methods generally decreased the counts of mesophilic and psychrotrophic bacteria and yeast molds and restricted the formation of thiobarbituric acid reactive substances and biogenic amines. Heat mapping, PCA, and multivariate analysis methods confirmed chemical analysis results. The volatile compounds were at their highest levels in the control samples at the end of storage, followed by H2, N2, H2-P-Mg, and VP samples. Using the H2-P-Mg method in MBM preparation could protect the quality characteristics and safety of the product during cold storage.

Glucose breath test for the detection of small intestine bacterial overgrowth: Impact of diet prior to the test.

BACKGROUND: Glucose breath test (GBT) is used for the diagnosis of small intestine bacterial overgrowth. A restrictive diet without fibers and/or fermentable food is recommended on the day before the test. The aim of our retrospective study was to evaluate the impact of two different restrictive diets on the results of GBT. METHODS: A change of the pretest restrictive diet was applied in our lab on September 1, 2020. The recommended diet was a fiber-free diet before this date, and a fiber-free diet plus restriction of all fermentable food afterward. We thus compared the results of GBT performed before (group A) and after (group B) this pretest diet modification. Demographics, reasons to perform GBT, digestive symptoms, and hydrogen and methane baseline values and variations after glucose ingestion were compared between the two groups. KEY RESULTS: 269 patients underwent GBT in group A, and 316 patients in group B. The two groups were comparable in terms of demographics. Methane and hydrogen baseline values were significantly higher in group A (respectively 14 [18] vs. 8 [14] ppm, p < 0.01 and 11 [14] vs. 6 [8] ppm, p < 0.01). The percentage of positive tests was higher in group A for methane (43% vs. 28%, p < 0.05), and for hydrogen (18% vs. 12%, p = 0.03). CONCLUSION & INFERENCES: This retrospective study suggests the importance of the restrictive diet prior to GBT. A strict limitation of fibers and fermentable food decreased hydrogen and methane baseline values, and the prevalence of positive GBT. Thus a strict restrictive diet should be recommended on the day before the test, in order to limit the impact of food on hydrogen and methane breath levels, and possibly improve the diagnosis quality of GBT.

Continuous planting of Chinese fir monocultures significantly influences dissolved organic matter content and microbial assembly processes.

Monoculture plantations in China, characterized by the continuous cultivation of a single species, pose challenges to timber accumulation and understory biodiversity, raising concerns about sustainability. This study investigated the impact of continuous monoculture plantings of Chinese fir (Cunninghamia lanceolata [Lamb.] Hook.) on soil properties, dissolved organic matter (DOM), and microorganisms over multiple generations. Soil samples from first to fourth-generation plantations were analyzed for basic chemical properties, DOM composition using Fourier transform ion cyclotron resonance mass spectrometry, and microorganisms via high-throughput sequencing. Results revealed a significant decline in nitrate nitrogen content with successive rotations, accompanied by an increase in easily degradable compounds like carbohydrates, aliphatic/proteins, tannins, Carbon, Hydrogen, Oxygen and Nitrogen- (CHON) and Carbon, Hydrogen, Oxygen and Sulfur- (CHOS) containing compounds. However, the recalcitrant compounds, such as lignin and carboxyl-rich alicyclic molecules (CRAMs), condensed aromatics and Carbon, Hydrogen and Oxygen- (CHO) containing compounds decreased. Microorganism diversity, abundance, and structure decreased with successive plantations, affecting the ecological niche breadth of fungal communities. Bacterial communities were strongly influenced by DOM composition, particularly lignin/CRAMs and tannins. Continuous monoculture led to reduced soil nitrate, lignin/CRAMs, and compromised soil quality, altering chemical properties and DOM composition, influencing microbial community assembly. This shift increased easily degraded DOM, accelerating soil carbon and nitrogen cycling, ultimately reducing soil carbon sequestration. From environmental point of view, the study emphasizes the importance of sustainable soil management practices in continuous monoculture systems. Particularly the findings offer valuable insights for addressing challenges associated with monoculture plantations and promoting long-term ecological sustainability.

Strategies to enhance biohydrogen production from microalgae: A comprehensive review.

Microalgae represent a promising renewable feedstock for the sustainable production of biohydrogen. Their high growth rates and ability to fix carbon utilizing just sunlight, water, and nutrients make them well-suited for this application. Recent advancements have focused on improving microalgal hydrogen yields and cultivation methods. This review aims to summarize recent developments in microalgal cultivation techniques and genetic engineering strategies for enhanced biohydrogen production. Specific areas of focus include novel microalgal species selection, immobilization methods, integrated hybrid systems, and metabolic engineering. Studies related to microalgal strain selection, cultivation methods, metabolic engineering, and genetic manipulations were compiled and analyzed. Promising microalgal species with high hydrogen production capabilities such as Synechocystis sp., Anabaena variabilis, and Chlamydomonas reinhardtii have been identified. Immobilization techniques like encapsulation in alginate and integration with dark fermentation have led to improved hydrogen yields. Metabolic engineering through modulation of hydrogenase activity and photosynthetic pathways shows potential for enhanced biohydrogen productivity. Considerable progress has been made in developing microalgal systems for biohydrogen. However, challenges around process optimization and scale-up remain. Future work involving metabolic modeling, photobioreactor design, and genetic engineering of electron transfer pathways could help realize the full potential of this renewable technology.

Added Value of 13C Analysis in Breath Tests in H2-Negative Subjects to Diagnose Lactose Malabsorption: A Proof of Concept Study.

INTRODUCTION: Diagnosing lactose malabsorption is usually based on hydrogen excretion in breath after a lactose challenge. However, a proportion of subjects with lactose malabsorption will not present a rise in hydrogen. Measuring excretion of methane or stable isotope labeled 13CO2 after ingestion of 13C-lactose has been proposed to mitigate this problem. OBJECTIVE: The aim of the study was to assess the performance of measuring methane and 13CO2 in individuals with normal hydrogen excretion compared to a genetic lactase non-persistence test. METHODS: Individuals referred for lactose breath testing and healthy controls were included. Participants received 13C-enriched lactose, performed breath testing, and underwent genotyping for a marker of lactase non-persistence (13910C*T). Using genotype as gold standard, the performance of measuring methane and 13CO2 excretion was assessed. RESULTS: 151 subjects participated in the study, 50 of which presented a lactase non-persistent genotype. Of these, 72% were correctly diagnosed through hydrogen excretion of ≥ 20 ppm above baseline. In subjects with normal hydrogen excretion, cumulative 13C excretion had an area under the curve (AUC) of the receiver operating characteristics (ROC) curve of 0.852. Sensitivity was 93% and specificity was 51% for the current cutoff of 14.5%. The optimal cutoff was 12.65% (sensitivity 93%, specificity 70%). The ROC curve of peak methane had an AUC of 0.542 (sensitivity of 14%, specificity of 91% for cutoff ≥ 10 ppm). CONCLUSIONS: In individuals with genetically demonstrated lactase non-persistence and negative hydrogen breath test, the use of 13C-lactose with measurement of 13CO2 excretion and hydrogen is a well-performing test to detect the lactose malabsorption and performs better than methane in our cohort.