Nitrogen oxides(NOx=NO+NO2)are important precursors of ozone(O3),and NOx and its oxides together constitute reactive nitrogen oxides(NOy)in the atmosphere.A comprehensive understanding of the total NOy level in the atmosphere is of great significance for a deeper understanding of the atmospheric nitrogen cycle and oxidation,as well as for formulating strategies for air pollution prevention and control.In this work,a thermal decomposition-broadband cavity enhanced absorption spectroscopy(TD-BBCEAS)technique for online measurement of total NOy in the atmosphere was developed.With this method,the NOy was efficiently converted into NO2,and the total NOy concentration in the atmosphere was indirectly obtained by measuring NO2.Focusing on the key factors affecting the measurement of total NOy,the influence of NO titration efficiency and other NOy component TD efficiency on measurement accuracy was emphasized.By changing the oxygen(O2)flow rate through the mercury lamp to alter the O3 concentration for titrating NO,the conversion efficiency of NO was evaluated.At O2 flow rate of 6 mL/min,the conversion efficiency of NO was greater than 99%.TD efficiency testing and analysis on NO2,peroxyacetyl nitrate(PAN),nitric acid(HNO3),and nitrous acid(HONO),which account for a large proportion of atmospheric NOy components,was carried out using 680℃as the optimal TD temperature for efficient conversion of NOy.With NO and HONO sample gases as typical verification gases,the conversion efficiency of NOy and the accuracy of NOy measurement by TD-BBCEAS system were verified by switching the on and off modes of mercury lamp and TD device.At integration time of 60 s,the detection limit of the system for NOy was 2.83×1010 molecules/cm3(60 s,2σ).A comparative measurement of actual atmospheric NOy was conducted between the TD-BBCEAS system and the NOy analyzer.The observation results showed a correlation coefficient(R2)of 0.98 and a slope of 0.93,further verifying the feasibility and accuracy of applying the TD-BBCEAS system to measurement of total NOy.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: To explore short-term clinical efficacy of minimally invasive diagnosis and treatment system for hallux valgus in guiding the treatment of hallux valgus. METHODS: From March 2021 to November 2023, 68 patients (136 feet) with hallux valgus were treated under guidance of minimally invasive diagnosis and treatment system, including 12 males and 56 females;aged from 25 to 68 years old with an average of (42.5±8.5) years old, the course of disease ranged from 3.2 to 15.6 years with an average of (10.3±2.6) years. The changes of hallux valgus angle (HVA) and intermetatarsal angle (IMA), visual analog scale (VAS) and American Orthopaedic Foot Ankle Society (AOFAS) forefoot score were recorded and compared before operation and 12 months after operation. RESULTS: Sixty-five patients (130 feet) were followed up for 12 to 15 months with an average of (13.8±0.5) months, 3 patients (6 feet) were not followed up as required. HVA and IMA improved from (35.5±3.5) ° and (12.5±2.0) ° before operation to (10.5±2.5) ° and (8.5±1.5) °12 months after operation, respectively, with statistically significant differences (P<0.05);VAS decreased from (5.5±1.2) before operation to (1.2±0.5) at 12 months after operation, and the difference was statistically significant (P<0.05);AOFAS forefoot score increased from (50.6±5.1) before operation to (93.8±5.6) at 12 months after operation, with a statistically significant difference (P<0.05). Among them, 102 feet were got excellent result, 24 feet good, and 4 feet fair. Two patients were developed calf intermuscular vein thrombosis, and were cured after 3 months of symptomatic treatment. CONCLUSION Under the guidance of minimally invasive diagnosis and treatment system for hallux valgus, the treatment of HV could obviously improve HVA and IMA, and significantly alleviate pain symptoms, and accelerate functional recovery.
Humans ; Hallux Valgus/diagnosis* ; Male ; Female ; Middle Aged ; Adult ; Aged ; Minimally Invasive Surgical Procedures/methods* ; Treatment Outcome

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged

With the extension of the global population's lifespan and the increasingly severe aging problem,cardio-vascular diseases have become the leading cause of death among the elderly population.Most cardiovascular diseases orig-inate from the formation of atherosclerotic plaques.In addition to common risk factors such as dyslipidemia,diabetes,hy-pertension,smoking,and obesity,circadian rhythm disruption is also regarded as an important but often overlooked risk factor for atherosclerosis.The circadian rhythm is involved in regulating key physiological processes such as inflammation and metabolism,which in turn affect the pathological processes of arteriosclerosis and thrombosis.In this process,the key genes that maintain the stability of the circadian rhythm,namely clock gene,play a crucial role.Clock gene have an important role in the pathological mechanism of atherosclerosis,and they may become potential new targets for the preven-tion and treatment of atherosclerosis.This paper reviews the latest research progress on the mechanism of action of clock gene in the occurrence and development of atherosclerosis.These findings may provide new ideas for the diagnosis and treatment of atherosclerosis.

The primary role of transfer RNA(tRNA)is to connect a specific amino acid to its 3' end, use its anticodon to match the codon on messenger RNA(mRNA), and deliver the corresponding amino acid to the ribosome for protein synthesis.tRNA exists in two forms: precursor tRNA and mature tRNA.When acted upon by enzymes like Dicer, elaC ribonuclease Z 2(ELAC2), angiopoietin(ANG), and other ribonucleases, tRNA is broken down into tRNA-derived stress-induced RNA(tiRNA)and tRNA-derived fragments(tRF).Recent advancements in RNA sequencing technology have led to increased interest in tiRNA and tRF, shedding light on their roles in various physiological and pathological processes.tRNA-derived small molecules(tsRNA)function similarly to microRNA(miRNA), influencing gene expression and protein synthesis.They show promise as diagnostic markers and potential therapeutic targets for age-related diseases.This review offers a comprehensive analysis of tsRNA classification, biological functions, research advancements, and clinical applications in age-related conditions.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

The primary role of transfer RNA(tRNA)is to connect a specific amino acid to its 3' end, use its anticodon to match the codon on messenger RNA(mRNA), and deliver the corresponding amino acid to the ribosome for protein synthesis.tRNA exists in two forms: precursor tRNA and mature tRNA.When acted upon by enzymes like Dicer, elaC ribonuclease Z 2(ELAC2), angiopoietin(ANG), and other ribonucleases, tRNA is broken down into tRNA-derived stress-induced RNA(tiRNA)and tRNA-derived fragments(tRF).Recent advancements in RNA sequencing technology have led to increased interest in tiRNA and tRF, shedding light on their roles in various physiological and pathological processes.tRNA-derived small molecules(tsRNA)function similarly to microRNA(miRNA), influencing gene expression and protein synthesis.They show promise as diagnostic markers and potential therapeutic targets for age-related diseases.This review offers a comprehensive analysis of tsRNA classification, biological functions, research advancements, and clinical applications in age-related conditions.

Objective To establish a sensitive,accurate and rapid detection method for 10 drugs and metabolites in hair with triple quadrupole tandem mass spectrometry,addressing the identification of drugs in real hair samples.Methods After cryogenic grinding and ultrasonic extraction,hair was separated by Restek Allure PFPP column(100 mm × 2.1 mm,5 μm).The mobile phase A was 20 mmol/L ammonium acetate,0.1％formic acid and 5％acetonitrile aqueous solution.The mobile phase B was acetonitrile.An electrospray ionization source was used for data acquisition in scheduled MRM mode.Results The method showed good linearity for all analytes within the validated range(R2＞0.995),with the limits of detection ranging from 0.5 to 6 pg/mg,the limits of quantification ranging from 2.5 to 10 pg/mg.Accuracy ranged from 89.1％to 114.6％,with intra-day precision ranging from 0.2％to 11.7％,inter-day precision ranging from 4.0％to 15.8％.the matrix effects ranging from 89.4％to 118.4％,the recoveries ranging from 63.6％～112.1％.Totally 20 cases were detected positive in 196 actual hair samples.Conclusion The time-scheduled scanning method exhibits high stability and sensitivity,enabling high-throughput detection,and is suitable for forensic toxicology laboratories to identify drugs in hair.