Chlorination of Aromatic Amino Acids: Elucidating Disinfection Byproducts, Reaction Kinetics, and Influence Factors.

In the face of ongoing water pollution challenges, the intricate interplay between dissolved organic matter and disinfectants like chlorine gives rise to potentially harmful disinfection byproducts (DBPs) during water treatment. The exploration of DBP formation originating from amino acids (AA) is a critical focus of global research. Aromatic DBPs, in particular, have garnered considerable attention due to their markedly higher toxicity compared to their aliphatic counterparts. This work seeks to advance the understanding of DBP formation by investigating chlorination disinfection and kinetics using tyrosine (Tyr), phenylalanine (Phe), and tryptophan (Trp) as precursors. Via rigorous experiments, a total of 15 distinct DBPs with accurate molecular structures were successfully identified. The chlorination of all three AAs yielded highly toxic chlorophenylacetonitriles (CPANs), and the disinfectant dosage and pH value of the reaction system potentially influence chlorination kinetics. Notably, Phe exhibited the highest degradation rate compared to Tyr and Trp, at both the CAA:CHOCl ratio of within 1:2 and a wide pH range (6.0 to 9.0). Additionally, a neutral pH environment triggered the maximal reaction rates of the three AAs, while an acidic condition may reduce their reactivity. Overall, this study aims to augment the DBP database and foster a deeper comprehension of the DBP formation and relevant kinetics underlying the chlorination of aromatic AAs.

Menin Deficiency Induces Autism-Like Behaviors by Regulating Foxg1 Transcription and Participates in Foxg1-Related Encephalopathy.

FOXG1 syndrome is a developmental encephalopathy caused by FOXG1 (Forkhead box G1) mutations, resulting in high phenotypic variability. However, the upstream transcriptional regulation of Foxg1 expression remains unclear. This report demonstrates that both deficiency and overexpression of Men1 (protein: menin, a pathogenic gene of MEN1 syndrome known as multiple endocrine neoplasia type 1) lead to autism-like behaviors, such as social defects, increased repetitive behaviors, and cognitive impairments. Multifaceted transcriptome analyses revealed that Foxg1 signaling is predominantly altered in Men1 deficiency mice, through its regulation of the Alpha Thalassemia/Mental Retardation Syndrome X-Linked (Atrx) factor. Atrx recruits menin to bind to the transcriptional start region of Foxg1 and mediates the regulation of Foxg1 expression by H3K4me3 (Trimethylation of histone H3 lysine 4) modification. The deficits observed in menin deficient mice are rescued by the over-expression of Foxg1, leading to normalized spine growth and restoration of hippocampal synaptic plasticity. These findings suggest that menin may have a putative role in the maintenance of Foxg1 expression, highlighting menin signaling as a potential therapeutic target for Foxg1-related encephalopathy.

Chloramine Disinfection of Levofloxacin and Sulfaphenazole: Unraveling Novel Disinfection Byproducts and Elucidating Formation Mechanisms for an Enhanced Understanding of Water Treatment.

The unrestricted utilization of antibiotics poses a critical challenge to global public health and safety. Levofloxacin (LEV) and sulfaphenazole (SPN), widely employed broad-spectrum antimicrobials, are frequently detected at the terminal stage of water treatment, raising concerns regarding their potential conversion into detrimental disinfection byproducts (DBPs). However, current knowledge is deficient in identifying the potential DBPs and elucidating the precise transformation pathways and influencing factors during the chloramine disinfection process of these two antibiotics. This study conducts a comprehensive analysis of reaction pathways, encompassing piperazine ring opening/oxidation, Cl-substitution, OH-substitution, desulfurization, and S-N bond cleavage, during chloramine disinfection. Twelve new DBPs were identified in this study, exhibiting stability and persistence even after 24 h of disinfection. Additionally, an examination of DBP generation under varying disinfectant concentrations and pH values revealed peak levels at a molar ratio of 25 for LEV and SPN to chloramine, with LEV contributing 11.5% and SPN 23.8% to the relative abundance of DBPs. Remarkably, this research underscores a substantial increase in DBP formation within the molar ratio range of 1:1 to 1:10 compared to 1:10 to 1:25. Furthermore, a pronounced elevation in DBP generation was observed in the pH range of 7 to 8. These findings present critical insights into the impact of the disinfection process on these antibiotics, emphasizing the innovation and significance of this research in assessing associated health risks.

Menin Reduces Parvalbumin Expression and is Required for the Anti-Depressant Function of Ketamine.

Dysfunction of parvalbumin (PV) neurons is closely involved in depression, however, the detailed mechanism remains unclear. Based on the previous finding that multiple endocrine neoplasia type 1 (Protein: Menin; Gene: Men1) mutation (G503D) is associated with a higher risk of depression, a Menin-G503D mouse model is generated that exhibits heritable depressive-like phenotypes and increases PV expression in brain. This study generates and screens a serial of neuronal specific Men1 deletion mice, and found that PV interneuron Men1 deletion mice (PcKO) exhibit increased cortical PV levels and depressive-like behaviors. Restoration of Menin, knockdown PV expression or inhibition of PV neuronal activity in PV neurons all can ameliorate the depressive-like behaviors of PcKO mice. This study next found that ketamine stabilizes Menin by inhibiting protein kinase A (PKA) activity, which mediates the anti-depressant function of ketamine. These results demonstrate a critical role for Menin in depression, and prove that Menin is key to the antidepressant function of ketamine.

Safety and efficacy of remimazolam tosilate combined with low-dose fentanyl for procedural sedation in obese patients undergoing gastroscopy: study protocol for a single-centre, double-blind, randomised controlled trial.

INTRODUCTION: Obese patients are susceptible to hypoxaemia during procedural sedation. Propofol combined with low-dose opioids is commonly used as a sedation strategy, but it can exacerbate hypoxaemia by causing cardiopulmonary depression and airway obstruction, especially in obese patients. Remimazolam, a novel ultra-short-acting benzodiazepine, has minimal accumulative effects and less cardiorespiratory depression. This study aims to evaluate the safety and efficacy of combining remimazolam tosilate with low-dose fentanyl as an alternative option for procedural sedation in obese patients undergoing gastroscopy. METHODS AND ANALYSIS: This randomised controlled trial (RCT) will be conducted in the Endoscopy Centre of the First Affiliated Hospital of Xiamen University, recruiting 174 participants scheduled for painless gastroscopy with a body mass index of 30-39.9 kg×m-2. All patients will be randomly divided into two groups in a 1:1 ratio. The sedation strategy of the intervention group is remimazolam tosilate combined with fentanyl, while the control group is propofol combined with fentanyl. The primary outcome is the incidence of hypoxaemia and the secondary outcomes include the time to ambulation, need for airway manoeuvres and rescue sedation, sleep quality, the incidence of sedation failure, adverse events and the cost of sedatives. All statistical tests will be performed using IBM SPSS V.20.0 statistical software. A p value<0.05 is considered statistically significant. ETHICS AND DISSEMINATION: This RCT was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Xiamen University (Scientific Research Ethics Review 2022, No.093). The results will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ChiCTR2200067076.

Modeling and calibration of micro/nano FBG temperature probe for scanning probe microscopy.

To accurately measure the local temperatures of the micro-nano area, we propose an optical method using a tapered fiber Bragg grating (FBG) probe with a nano tip for scanning probe microscopy (SPM). When the tapered FBG probe senses local temperature through near-field heat transfer, the intensity of the reflected spectrum decreases, along with a broadening bandwidth and a shift in the central peak position. Modeling the heat transfer between the probe and the sample shows that the tapered FBG probe is in a non-uniform temperature field when approaching the sample surface. Simulation of the probe's reflection spectrum reveals that the central peak position shifts nonlinearly with increasing local temperature. In addition, the near-field temperature calibration experiments show that the temperature sensitivity of the FBG probe increases nonlinearly from 6.2 pm/°C to 9.4 pm/°C as the sample surface temperature increases from 25.3°C to 160.4°C. The agreement of the experimental results with the theory and the reproducibility demonstrate that this method offers a promising approach for exploring micro-nano temperature.

Real-world emission characteristics and inventory of volatile organic compounds originating from construction and agricultural machinery.

Volatile organic compound (VOC) emissions originating from nonroad mobile sources constitute an important but uncertain source of secondary organic aerosols (SOAs) and ozone (O3). In this study, we investigated the emission factors (EFs) of 120 individual VOC species for 40 machines via gas chromatography-mass spectrometry/flame ionization detection and high-performance liquid chromatography. The results showed that the diesel-based VOC EF for the tested machines was 4.18 ± 2.55 (average ± standard deviation) g/kg fuel, dominated by alkanes (38.20 % ± 18.08 %) and oxygenated VOCs (OVOCs; 30.94 % ± 15.71 %). The machine type, rated power, emission standards, and operating conditions affected the emissions of VOCs and their components, and this effect maybe mostly depends on the fuel combustion efficiency. The VOC species were primarily distributed in the C1-C2 and C4-C6 (based on the carbon number) and B4-B6 (based on the saturated vapor concentration) intervals. Furthermore, the estimated formation potential (FP) values of SOAs and O3 from VOCs were 21.02 ± 15.57 mg/kg fuel and 15.96 ± 11.87 g/kg fuel, respectively. VOC control based on the SOA formation potential (SOAFP) and ozone formation potential (OFP) could be more effective in the mitigation of fine particulate matter (PM2.5) and O3 pollution because the top 5 species ranked by percentage contribution accounted for 83.09 % ± 9.59 % and 51.78 % ± 14.38 % of the estimated SOAFP and OFP, respectively. Finally, the emission estimates showed that the VOC emissions originating from construction and agricultural machinery in China (2020) reached 64.05 and 95.24 Gg, respectively. We provide species-specific VOC EFs and detailed emission characteristics to facilitate a comprehensive understanding of gas emissions originating from nonroad mobile sources and an update of emission inventories and atmospheric chemistry models.

Highly efficient method for cutting position selection of an x-ray mono-capillary lens based on an improved SCA-CSA algorithm.

In order to efficiently select the optimal cutting position of x-ray mono-capillary lenses, an improved sine cosine algorithm-crow search algorithm (SCA-CSA) algorithm is proposed, which combines the sine cosine algorithm with the crow search algorithm, with further enhancements. The fabricated capillary profile is measured using an optical profiler; then the surface figure error for interest regions of the mono-capillary can be evaluated using the improved SCA-CSA algorithm. The experimental results indicate that the surface figure error in the final capillary cut region is about 0.138 µm, and the runtime is 2.284 s. When compared with the traditional metaheuristic algorithm, the particle swarm optimization algorithm, the improved SCA-CSA algorithm, enhances the surface figure error metric by two orders of magnitude. Furthermore, the standard deviation index of the surface figure error metric for 30 runs also improves by more than 10 orders of magnitude, demonstrating the superior performance and robustness of the algorithm. The proposed method provides significant support for the development of precise cuttings of mono-capillaries.

Application of Indocyanine Green Fluorescence Imaging in Assisting Biopsy of Musculoskeletal Tumors.

(1) Background: Biopsies are the gold standard for the diagnosis of musculoskeletal tumors. In this study, we aimed to explore whether indocyanine green near-infrared fluorescence imaging can assist in the biopsy of bone and soft tissue tumors and improve the success rate of biopsy. (2) Method: We recruited patients with clinically considered bone and soft tissue tumors and planned biopsies. In the test group, indocyanine green (0.3 mg/kg) was injected. After identifying the lesion, a near-infrared fluorescence camera system was used to verify the ex vivo specimens of the biopsy in real time. If the biopsy specimens were not developed, we assumed that we failed to acquire lesions, so the needle track and needle position were adjusted for the supplementary biopsy, and then real-time imaging was performed again. Finally, we conducted a pathological examination. In the control group, normal biopsy was performed. (3) Results: The total diagnosis rate of musculoskeletal tumors in the test group was 94.92% (56/59) and that in the control group was 82.36% (42/51). In the test group, 14 cases were not developed, as seen from real-time fluorescence in the core biopsy, and then underwent the supplementary biopsy after changing the puncture direction and the location of the needle channel immediately, of which 7 cases showed new fluorescence. (4) Conclusions: Using the near-infrared fluorescence real-time development technique to assist the biopsy of musculoskeletal tumors may improve the accuracy of core biopsy and help to avoid missed diagnoses, especially for some selected tumors.

DecouplingNet: A Stable Knowledge Distillation Decoupling Net for Fault Detection of Rotating Machines Under Varying Speeds.

Fault detection, also known as anomaly detection (AD), is at the heart of prediction and health management (PHM), which plays a vital role in ensuring the safe operation of mechanical equipment. Nonetheless, the lack of anomaly data creates a significant obstacle to the AD of the mechanical system. In particular, the complex modulation effects induced by time-varying speeds make AD much more challenging. For rapid and accurate AD, a stable knowledge distillation decoupling net (DecouplingNet) is provided to overcome these difficulties. First, an adversarial network consisting of an encoder, a decoder, and an encoder-discriminator is developed to model normal samples well by imposing constraints on the latent space. Then, a causal decoupling framework is suggested to disentangle equipment state-related information from operating conditions-related features, enabling stable condition monitoring at varying speeds. Finally, feature-based knowledge distillation is employed to boost the efficiency of AD while maintaining the detection accuracy. The proposed method is tested on two experimental scenarios and compared with some typical AD methods. The finding demonstrates that the net outperforms others in terms of accuracy and efficiency when it comes to detecting anomalies in the mechanical equipment that runs under varying speeds.

Hypothalamic Menin regulates systemic aging and cognitive decline.

Aging is a systemic process, which is a risk factor for impaired physiological functions, and finally death. The molecular mechanisms driving aging process and the associated cognitive decline are not fully understood. The hypothalamus acts as the arbiter that orchestrates systemic aging through neuroinflammatory signaling. Our recent findings revealed that Menin plays important roles in neuroinflammation and brain development. Here, we found that the hypothalamic Menin signaling diminished in aged mice, which correlates with systemic aging and cognitive deficits. Restoring Menin expression in ventromedial nucleus of hypothalamus (VMH) of aged mice extended lifespan, improved learning and memory, and ameliorated aging biomarkers, while inhibiting Menin in VMH of middle-aged mice induced premature aging and accelerated cognitive decline. We further found that Menin epigenetically regulates neuroinflammatory and metabolic pathways, including D-serine metabolism. Aging-associated Menin reduction led to impaired D-serine release by VMH-hippocampus neural circuit, while D-serine supplement rescued cognitive decline in aged mice. Collectively, VMH Menin serves as a key regulator of systemic aging and aging-related cognitive decline.

Predictive Models of Gas/Particulate Partition Coefficients (KP) for Polycyclic Aromatic Hydrocarbons and Their Oxygen/Nitrogen Derivatives.

Polycyclic aromatic hydrocarbons (PAHs) and their oxygen/nitrogen derivatives released into the atmosphere can alternate between a gas phase and a particulate phase, further affecting their environmental behavior and fate. The gas/particulate partition coefficient (KP) is generally used to characterize such partitioning equilibrium. In this study, the correlation between log KP of fifty PAH derivatives and their n-octanol/air partition coefficient (log KOA) was first analyzed, yielding a strong linear correlation (R2 = 0.801). Then, Gaussian 09 software was used to calculate quantum chemical descriptors of all chemicals at M062X/6-311+G (d,p) level. Both stepwise multiple linear regression (MLR) and support vector machine (SVM) methods were used to develop the quantitative structure-property relationship (QSPR) prediction models of log KP. They yield better statistical performance (R2 > 0.847, RMSE < 0.584) than the log KOA model. Simulation external validation and cross validation were further used to characterize the fitting performance, predictive ability, and robustness of the models. The mechanism analysis shows intermolecular dispersion interaction and hydrogen bonding as the main factors to dominate the distribution of PAH derivatives between the gas phase and particulate phase. The developed models can be used to predict log KP values of other PAH derivatives in the application domain, providing basic data for their ecological risk assessment.

Microglial hexokinase 2 deficiency increases ATP generation through lipid metabolism leading to ß-amyloid clearance.

Microglial cells consume adenosine triphosphate (ATP) during phagocytosis to clear neurotoxic ß-amyloid in Alzheimer's disease (AD). However, the contribution of energy metabolism to microglial function in AD remains unclear. Here, we demonstrate that hexokinase 2 (HK2) is elevated in microglia from an AD mouse model (5xFAD) and AD patients. Genetic deletion or pharmacological inhibition of HK2 significantly promotes microglial phagocytosis, lowers the amyloid plaque burden and attenuates cognitive impairment in male AD mice. Notably, the ATP level is dramatically increased in HK2-deficient or inactive microglia, which can be attributed to a marked upregulation in lipoprotein lipase (LPL) expression and subsequent increase in lipid metabolism. We further show that two downstream metabolites of HK2, glucose-6-phosphate and fructose-6-phosphate, can reverse HK2-deficiency-induced upregulation of LPL, thus supporting ATP production and microglial phagocytosis. Our findings uncover a crucial role for HK2 in phagocytosis through regulation of microglial energy metabolism, suggesting a potential therapeutic strategy for AD by targeting HK2.

Disordered mullite grains in a sapphire-derived fiber for high-temperature sensing.

In this study, a sapphire-derived fiber (SDF)-based Fabry-Pérot interferometer (FPI) is proposed and experimentally demonstrated as a high-temperature sensor using the arc discharge crystallization process, forming a region with disordered mullite grains. This shows that the disordered mullite grains are related to the gradual temperature distribution during the arc discharge process, which results in a larger refractive index (RI) modulation of the SDF near the fusing area, forming a reflection mirror. An FPI was obtained by combining the optical fiber end facet. Considering the high-temperature resistance of the fiber, the fabricated FPI was used for high-temperature sensing. This shows that the device can operate at temperatures of up to 1200 °C with a sensitivity of 15.47 pm/°C, demonstrating that the proposed devices have potential applications in high-temperature environments.

Stag beetle Cyclommatus mniszechi employs both mutual- and self-assessment strategies in male-male combat.

Animals may base contest decisions on their fighting ability alone (self-assessment) or also their opponents' (mutual assessment). Many male stag beetles develop disproportionately enlarged mandibles and use them as weapons. Information on their assessment strategy is limited. To investigate their assessment strategy and whether they adopt the same strategy at different stages of contests, we used food to encourage male Cyclommatus mniszechi of different (random pairings) or similar (ML-matched pairings) mandible length (ML) to interact. For the random pairings, losers had shorter mandibles than winners and were faster to feed. Overall contest duration and the tendency to escalate to tussles associated positively with winners' ML and average ML in the random and the ML-matched pairings, respectively, consistent with self-assessment. Non-tussle phase duration associated positively with average ML in the ML-matched pairings, consistent with self-assessment. Tussle phase duration, however, positively associated with losers' ML in the random pairings and had no association with average ML in the ML-matched pairings, consistent with mutual assessment. These results show that (1) the males employ both assessment strategies, (2) winners have more control over contest intensity than losers, and (3) males with shorter mandibles are quicker to feed and also more likely to lose fights.

Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features.

In recent years, the use of Artificial Intelligence for emotion recognition has attracted much attention. The industrial applicability of emotion recognition is quite comprehensive and has good development potential. This research uses voice emotion recognition technology to apply it to Chinese speech emotion recognition. The main purpose of this research is to transform gradually popularized smart home voice assistants or AI system service robots from a touch-sensitive interface to a voice operation. This research proposed a specifically designed Deep Neural Network (DNN) model to develop a Chinese speech emotion recognition system. In this research, 29 acoustic characteristics in acoustic theory are used as the training attributes of the proposed model. This research also proposes a variety of audio adjustment methods to amplify datasets and enhance training accuracy, including waveform adjustment, pitch adjustment, and pre-emphasize. This study achieved an average emotion recognition accuracy of 88.9% in the CASIA Chinese sentiment corpus. The results show that the deep learning model and audio adjustment method proposed in this study can effectively identify the emotions of Chinese short sentences and can be applied to Chinese voice assistants or integrated with other dialogue applications.

Progresses in Fluorescence Imaging Guidance for Bone and Soft Tissue Sarcoma Surgery.

R0 surgical resection is the preferred treatment for bone and soft tissue sarcoma. However, there is still a lack of precise technology that can visualize bone and soft tissue sarcoma during surgery to assist the surgeon in judging the tumor surgical boundary. Fluorescence imaging technology has been used in the diagnosis of cancer. It is a simple and essentially safe technique that takes no additional time during the operation. Intraoperative fluorescence imaging has potential application prospects in assisting the surgeons in judging the tumor boundary and improving the accuracy of surgical resection. This review mainly starts with clinical studies, animal experimentation, and newly designed probes of intraoperative fluorescence imaging of bone and soft tissue sarcoma, to appraise the application prospects of fluorescence imaging technology in bone and soft tissue sarcoma.

CEND1 deficiency induces mitochondrial dysfunction and cognitive impairment in Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of neurodegenerative disease featured with memory loss and cognitive function impairments. Chronic mitochondrial stress is a vital pathogenic factor for AD and finally leads to massive neuronal death. However, the underlying mechanism is unclear. By proteomic analysis, we identified a new mitochondrial protein, cell-cycle exit and neuronal differentiation 1 (CEND1), which was decreased significantly in the brain of 5xFAD mice. CEND1 is a neuronal specific protein and locates in the presynaptic mitochondria. Depletion of CEND1 leads to increased mitochondrial fission mediated by upregulation of dynamin related protein 1 (Drp1), resulting in abnormal mitochondrial functions. CEND1 deficiency leads to cognitive impairments in mice. Overexpression of CEND1 in the hippocampus of 5xFAD mice rescued cognitive deficits. Moreover, we identified that CDK5/p25 interacted with and phosphorylated CEND1 which promoted its degradation. Our study provides new mechanistic insights in mitochondrial function regulations by CEND1 in Alzheimer's disease.

Monitoring Junction Temperature of RF MOSFET under Its Working Condition Using Fiber Bragg Grating.

When a high-power radio frequency (RF) metal oxide semiconductor field effect transistor (MOSFET) works in low-efficiency situations, considerable power is dissipated into heat, resulting in an excessive junction temperature and a likely failure. In this study, an optical fiber Bragg grating (FBG) sensor is installed on the die of a high-power RF MOSFET. The temperature change of RF MOSFET with the change of input signal is obtained by using the temperature frequency shift characteristic of the FBG reflected signal. Furthermore, the fast and repetitive capture of junction temperature by FBG reveals details of the temperature variation within each RF pulse, which is correctly correlated with input signals. The results show that besides monitoring the temperature accumulation of the chip for a long time, the FBG can also capture junction temperature details of the chip within each pulse period. Finally, a Cauer-type thermal model of the RF MOSFET was constructed based on the temperature information captured by the FBG.