Invasive fungal infections (IFIs) have become prominent global health threats, escalating the burden on public health systems. The increasing occurrence of invasive fungal infections is due primarily to the extensive application of chemotherapy, immunosuppressive therapies, and broad-spectrum antifungal agents. At present, therapeutic practices utilize multiple categories of antifungal agents, such as azoles, polyenes, echinocandins, and pyrimidine analogs. Nevertheless, the clinical effectiveness of these treatments is progressively weakened by the emergence of drug resistance, thereby substantially restricting their therapeutic utility. Consequently, there is an imperative need to expedite the discovery of novel antifungal agents. This review seeks to present an exhaustive synthesis of novel antifungal drugs and candidate agents that are either under current clinical investigation or anticipated to progress into clinical evaluation. These emerging compounds exhibit unique benefits concerning their modes of action, antimicrobial spectra, and pharmacokinetic characteristics, potentially leading to improved therapeutic outcomes relative to conventional antifungal regimens. It is anticipated that these novel therapeutic agents will furnish innovative treatment modalities and enhance clinical outcomes in managing invasive fungal infections.

Objective:To investigate the value of machine learning models based on CT radiomics for predicting the outcome of neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC).Methods:A retrospective case series study was conducted. A total of 279 LAGC patients receiving NAC before surgery in Shanxi Province Cancer Hospital from January 2018 to November 2020 were included. According to a ratio of 7∶3, all patients were randomly divided into the training set (196 cases) and the validation set (83 cases). According to the tumor regression grade (TRG), the pathological grade was divided into the good response of NAC (GR) group (TRG 0-1, 55 cases) and the poor response of NAC (PR) group (TRG 2-3, 224 cases). The clinicopathological data of patients were collected, such as age, gender, differentiation degree, clinical T and N staging, carcinoembryonic antigen (CEA), and carbohydrate antigen 199 (CA199) level. Radiomics features were extracted from the enhanced CT images in the vein phase, and the features were screened by 3-step dimensionality reduction. And then 5 machine learning algorithms including logistic regression (LR), naive bayes (NB), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGB) were applied to build prediction models based on the CT radiomics. The receiver operating characteristic (ROC) curve and the decision analysis (DCA) curve were drawn to evaluate the predictive performance and clinical benefit of each model on the outcome of NAC in patients with LAGC.Results:Among 196 patients in the training set, there were 39 cases in GR group and 157 cases in PR group; among 83 patients in the validation set, there were 16 cases in GR group and 67 cases in PR group. There were no statistically significant differences in clinicopathological data of patients between the training and validation sets, or between GR and PR groups in the training and validation sets (all P > 0.05). A total of 102 radiomics features were extracted from region of interest of CT images in the vein phase, and 6 key features were finally selected including original_firstorder_10Percentile, original_firstorder_RoubustMeanAbsoluteDeviation, original_glcm_Idmn, original_glcm_MCC, original_ngtdm_Busyness, original_ngtdm_Contrast; and there were statistically significant differences in 6 features between the GR and PR groups (all P < 0.05). LR, NB, RF, SVM and XGB machine learning algorithms were used to construct 5 prediction models based on the CT radiomics. The area under ROC curve for NAC prediction in the training set was 0.553, 0.709, 0.668, 0.772 and 0.790, respectively; in the validation set was 0.662, 0.622, 0.683, 0.752 and 0.784, respectively. The model constructed by XGB showed the best comprehensive performance, and its accuracy, sensitivity and specificity was 0.771, 0.562 and 0.821, respectively. In the DCA of 5 machine learning models in the training set, XGB-based model provided a higher net benefit. Conclusions:Machine learning models based on enhanced CT radiomics in the vein phase have a high predictive efficacy in the outcome of NAC in LAGC patients before surgery and it helps make clinical personalized treatment decisions.

OBJECTIVE: To observe the effects of "olfactory three needles" on cognition, learning and memory abilities, as well as hippocampal microglia (MG) phagocytic activity in vascular dementia (VD) rats, and explore the mechanisms of acupuncture in regulating MG activation and improving remyelination, so as to ameliorate VD. METHODS: Among 38 SD rats meeting experimental requirements, 9 rats were randomly assigned to a sham-operation group, and the remaining rats underwent permanent bilateral common carotid artery ligation to establish VD model. Eighteen successfully modeled rats were randomly divided into a model group and an electroacupuncture (EA) group, with 9 rats in each one. In the EA group, EA was performed at "olfactory three needles" ("Yintang" [GV24⁺] and bilateral "Yingxiang" [LI20]), at disperse-dense wave, the frequency of 2 Hz/15 Hz and the current intensity of 1 mA, for 15 min per intervention, once daily. One course was composed of 7 days, and 2 courses were required, with the interval of 2 days. The novel object recognition test was employed to assess the cognition of rats, and the Morris water maze was adopted to observe learning and memory abilities. Luxol fast blue (LFB) staining was performed to evaluate myelin sheath loss in the hippocampus, the Western blot was used to detect the protein expression of triggering receptor expressed on myeloid cells-2 (TREM2) and proteolipid protein (PLP) in the hippocampus; and the immunofluorescence staining was used to detect the positive expression of PLP, sex determining region Y-box 10 (SOX10), ionized calcium binding adaptor molecule 1 (Iba1)⁺ TREM2⁺ and Iba1⁺ lysosome-associated membrane protein 1 (LAMP1)⁺ in the hippocampus. RESULTS: Compared with the sham-operation group, the rats in the model group exhibited the prolonged escape latency on day 3 and 4 (P<0.05, P<0.01), the increase of the total distance traveling (P<0.01) and the decrease of the recognition index (RI) and platform crossing frequency (P<0.01). Compared with the model group, the rats in the EA group showed the shortened escape latency on day 3 and 4 (P<0.05), the decrease of total distance traveling (P<0.01) and the increase of RI and platform crossing frequency (P<0.05, P<0.01). When compared with the sham-operation group, the rats of the model group presented uneven staining, sparse arrangement of myelin sheath fibers, unclear contours, and prominent vacuole-like changes in the hippocampal CA1 region. When compared with the model group, the EA group showed more dense staining, the increase of myelin sheath fibers with more orderly alignment, and fewer vacuolar changes in the hippocampal CA1 region. Compared with the sham-operation group, the model group exhibited the increase of TREM2 protein expression and the decrease of PLP protein expression in the hippocampus (P<0.01), whereas the EA group showed the up-regulation of TREM2 and PLP protein expression when compared with the model group (P<0.01, P<0.05). The positive expression of the hippocampal PLP, SOX10, and Iba1⁺LAMP1⁺ in the model group was reduced in comparison with the sham-operation group (P<0.05, P<0.01), and the positive expression of Iba1⁺ TREM2⁺ was elevated (P<0.05). In the EA group, the positive expression of PLP, SOX10, Iba1⁺TREM2⁺, and Iba1⁺ LAMP1⁺ was higher compared with that in the model group (P<0.05, P<0.01). CONCLUSION "Olfactory three needles" can improve the learning and memory, and cognitive functions of VD rats, and its mechanism may be associated with the up-regulation of TREM2 and LAMP1 to adjust MG phagocytic activity and intracellular degradation, and promote remyelination.
Animals ; Dementia, Vascular/metabolism* ; Rats ; Rats, Sprague-Dawley ; Microglia/metabolism* ; Male ; Acupuncture Therapy/instrumentation* ; Acupuncture Points ; Humans ; Remyelination ; Memory ; Hippocampus/cytology* ; Cognition ; Electroacupuncture ; Needles

Objective:To investigate the current situation and influencing factors of geriatric nursing competence of nursing students in the later stage of practice, and to provide reference for formulating the reform strategy of geriatric nursing teaching, carrying out nursing education intervention and improving students′ geriatric nursing competence.Methods:From December 2023 to February 2024, 361 students from 6 colleges and universities in Inner Mongolia Autonomous Region were investigated by using the questionnaire of geriatric nursing competence by convenient sampling method.Results:Therefore, 361 nursing students in the late stage of clinical practice who meta the inclusion and exclusion criteria were included, 65 males and 296 females with (21.20 ± 2.02) years. The total score of geriatric nursing competence was (164.47 ± 32.25). Learning motivation ( β=11.09, P<0.05), whether to participate in activities to serve the elderly ( β=10.03, P<0.05), and training level ( β=-4.42, P<0.05) were the influencing factors affecting the elderly care ability of nursing students in the later stage of practice, which explained 12.5% of total variance. Conclusions:The geriatric nursing competence of nursing students in the later stage of practice is generally at a medium level, and the ability of each dimension is not balanced. Nursing educators should enrich the content of geriatric nursing courses, pay attention to the practical activities of the elderly, stimulate students′ learning motivation, and promote the construction of training programs for the geriatric nursing competence of nursing students at different training levels, so as to improve students' geriatric nursing competence.

Objective:To investigate the current situation and influencing factors of geriatric nursing competence of nursing students in the later stage of practice, and to provide reference for formulating the reform strategy of geriatric nursing teaching, carrying out nursing education intervention and improving students′ geriatric nursing competence.Methods:From December 2023 to February 2024, 361 students from 6 colleges and universities in Inner Mongolia Autonomous Region were investigated by using the questionnaire of geriatric nursing competence by convenient sampling method.Results:Therefore, 361 nursing students in the late stage of clinical practice who meta the inclusion and exclusion criteria were included, 65 males and 296 females with (21.20 ± 2.02) years. The total score of geriatric nursing competence was (164.47 ± 32.25). Learning motivation ( β=11.09, P<0.05), whether to participate in activities to serve the elderly ( β=10.03, P<0.05), and training level ( β=-4.42, P<0.05) were the influencing factors affecting the elderly care ability of nursing students in the later stage of practice, which explained 12.5% of total variance. Conclusions:The geriatric nursing competence of nursing students in the later stage of practice is generally at a medium level, and the ability of each dimension is not balanced. Nursing educators should enrich the content of geriatric nursing courses, pay attention to the practical activities of the elderly, stimulate students′ learning motivation, and promote the construction of training programs for the geriatric nursing competence of nursing students at different training levels, so as to improve students' geriatric nursing competence.

Objective:To investigate the value of machine learning models based on CT radiomics for predicting the outcome of neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC).Methods:A retrospective case series study was conducted. A total of 279 LAGC patients receiving NAC before surgery in Shanxi Province Cancer Hospital from January 2018 to November 2020 were included. According to a ratio of 7∶3, all patients were randomly divided into the training set (196 cases) and the validation set (83 cases). According to the tumor regression grade (TRG), the pathological grade was divided into the good response of NAC (GR) group (TRG 0-1, 55 cases) and the poor response of NAC (PR) group (TRG 2-3, 224 cases). The clinicopathological data of patients were collected, such as age, gender, differentiation degree, clinical T and N staging, carcinoembryonic antigen (CEA), and carbohydrate antigen 199 (CA199) level. Radiomics features were extracted from the enhanced CT images in the vein phase, and the features were screened by 3-step dimensionality reduction. And then 5 machine learning algorithms including logistic regression (LR), naive bayes (NB), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGB) were applied to build prediction models based on the CT radiomics. The receiver operating characteristic (ROC) curve and the decision analysis (DCA) curve were drawn to evaluate the predictive performance and clinical benefit of each model on the outcome of NAC in patients with LAGC.Results:Among 196 patients in the training set, there were 39 cases in GR group and 157 cases in PR group; among 83 patients in the validation set, there were 16 cases in GR group and 67 cases in PR group. There were no statistically significant differences in clinicopathological data of patients between the training and validation sets, or between GR and PR groups in the training and validation sets (all P > 0.05). A total of 102 radiomics features were extracted from region of interest of CT images in the vein phase, and 6 key features were finally selected including original_firstorder_10Percentile, original_firstorder_RoubustMeanAbsoluteDeviation, original_glcm_Idmn, original_glcm_MCC, original_ngtdm_Busyness, original_ngtdm_Contrast; and there were statistically significant differences in 6 features between the GR and PR groups (all P < 0.05). LR, NB, RF, SVM and XGB machine learning algorithms were used to construct 5 prediction models based on the CT radiomics. The area under ROC curve for NAC prediction in the training set was 0.553, 0.709, 0.668, 0.772 and 0.790, respectively; in the validation set was 0.662, 0.622, 0.683, 0.752 and 0.784, respectively. The model constructed by XGB showed the best comprehensive performance, and its accuracy, sensitivity and specificity was 0.771, 0.562 and 0.821, respectively. In the DCA of 5 machine learning models in the training set, XGB-based model provided a higher net benefit. Conclusions:Machine learning models based on enhanced CT radiomics in the vein phase have a high predictive efficacy in the outcome of NAC in LAGC patients before surgery and it helps make clinical personalized treatment decisions.

With the continuous development of healthcare industry,hospital publicity plays a pivotal role in brand con-struction,image shaping,and fostering harmonious doctor-patient relationships.This article highlights the strategic approach of The First Affiliated Hospital/School of Clinical Medicine of Guangdong Pharmaceutical University to bolstering its correspondent team and enhancing its publicity efforts.By establishing a"1+2+3"working system--one principle,two systems,and three types of training--the goal is to build a correspondent team that is politically steadfast,high-quality,and dedicated.From 2021 to 2023,the hospital has witnessed a notable improvement in submissions from the correspondents.These advancements have not only elevated the hospital's media output but also significantly contributed to the broader dissemination of its publicity materials and the advancement of its brand identity.These efforts support the favorable development of news and public opinion within the health industry.

The angiogenic microenvironment is a new blood vessel with different molecular and functional characteristics that sprouts on the original blood vessels through different mechanisms,which directly affects the process of tumor cell growth,proliferation,and migration and has an important impact on the occurrence and development of precancerous lesions of gastric cancer.Correa mode has shown that precancerous lesions of gastric cancer is the key pathological stage before the occurrence of gastric cancer,and it is of great significance to advance the prevention and treatment strategy to this stage.TCM believes that qi deficiency and blood stasis is the key pathogenesis of precancerous lesions of gastric cancer,and its basic treatment is to replenish qi and remove blood stasis,and based on the syndrome differentiation,drugs with the efficacy of nourishing yin and tonifying stomach,soothing the liver and regulating qi,resolving phlegm and dispersing lumps,and clearing heat and dampness for treatment.This article discussed the correlation between precancerous lesions of gastric cancer and angiogenic microenvironment and its regulatory pathways,and summarized the methods and mechanisms of TCM in the treatment of precancerous lesions of gastric cancer from the perspective of regulating angiogenic microenvironment-related pathways,in order to provide a reference for the treatment of precancerous lesions of gastric cancer with TCM.

OBJECTIVE To study the in vitro transdermal characteristics of Tibetan new drugs hereinafter referred to as Zhengrutie cataplasm, and to evaluate the safety of skin medication by using different species of animals(guinea pigs, New Zealand rabbits). METHODS The improved vertical Franz diffusion cell method was used for in vitro transdermal testand the skin of Bama miniature pig was used as the permeation barrier. The cumulative permeation amount and rate of geniposide methyl ester and 8-O-acetyl geniposide methyl ester, borneol and camphor in the receiving medium were determined by HPLC and GC, respectively, to investigate the in vitro transdermal characteristics of Zhengrutie cataplasm. Buehler test was used to study the sensitization of Zhengrutie cataplasm on guinea pig skin. Observed the skin irritation after single or multiple application of Zhengrutie cataplasm on intact and damaged skin of New Zealand rabbits. RESULTS The cumulative permeation amount of the sum of geniposide methyl ester and 8-O-acetyl geniposide methyl ester, borneol and camphor within 24 h were 14.14, 348.21, 490.97 μg·cm-2, respectively. The cumulative permeation amount were 6.2%, 10.2% and 15.3%, respectively. The average permeation amount were 0.59, 14.51 and 20.46 μg·cm-2·h-1. No allergic reaction to guinea pig skin, no irritation to intact skin of New Zealand rabbits, mild irritation to damaged skin. CONCLUSION The in vitro transdermal performance of Zhengrutie cataplasm is good. The in vitro transdermal process conforms to the zero-order kinetic equation. It has no irritation and sensitization effect on the skin of guinea pigs and New Zealand rabbits. It is safe and reliable for skin external use and has good clinical application value.

Objective:Establishment of a new model of human primary colon cancer transplantation tumor in normal immune mice and to provide a reliable experimental animal model for studying the pathogenesis of colon cancer under normal immunity.Methods:Human colon cancer cells come from colon cancer patients who underwent surgery in the Affiliated Hospital of Jining Medical College in 2017. The mice in the cell control group were inoculated with phosphate buffered solution (PBS) containing colon cancer cells, the microcarrier control group was inoculated with PBS containing microcarrier 6, and the cell-microcarrier complex group was inoculated with the PBS containing colon cancer cell-microcarrier complex. The cells of each group were inoculated under the skin of the right axilla of mice by subcutaneous injection, and the time, size, tumor formation rate and pathological changes under microscope were recorded. The transplanted tumor tissue was immunohistochemically stained with the EnVisiion two-step method, and the tumor formation rate of the transplanted tumor was judged according to the proportion of positive cells in the visual field. The polymerase chain reaction (PCR) method was used to detect the expression of human-specific Alu sequence in mice tumor tissue.Results:After inoculation with tumor cells, the mice in the cell control group and the microcarrier control group did not die and did not form tumors; the mice in the cell-microcarrier complex group had palpable subcutaneous tumors in the right axillary subcutaneously on the 5th to 7th days after inoculation, and tumor formation rate is 67% (10/15), and the tumor volume can reach about 500 mm 3 2 to 3 weeks after vaccination. The immunohistochemistry results showed that CK20, CDX-2 and carcinoembryonic antigen were all positively expressed. The PCR results showed that the expression of human-specific Alu sequence can be detected in the transplanted tumor tissue of tumor-bearing mice. Conclusion:Human primary colon cancer cells used microcarrier 6 as a carrier to form tumors in normal immunized mice, and successfully established a new model of human colon cancer transplantation tumor in normal immune mice.