Category: Statistics

Zhongguo Zhong Yao Za Zhi. 2025 May;50(10):2865-2874. doi: 10.19540/j.cnki.cjcmm.20250212.502.

ABSTRACT

Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.

PMID:40686154 | DOI:10.19540/j.cnki.cjcmm.20250212.502

Zhongguo Zhong Yao Za Zhi. 2025 May;50(10):2740-2749. doi: 10.19540/j.cnki.cjcmm.20250114.401.

ABSTRACT

This study aims to explore the mechanism through which Yishen Jiangtang Decoction(YSJTD) regulates endoplasmic reticulum stress(ERS)-mediated NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome to improve diabetic nephropathy(DN) in db/db mice. Thirty db/db mice were randomly divided into the model group, YSJTD group, ERS inhibitor 4-phenylbutyric acid(4-PBA) group, with 10 mice in each group. Additionally, 10 db/m mice were selected as the control group. The YSJTD group was orally administered YSJTD at a dose of 0.01 mL·g~(-1), the 4-PBA group was orally administered 4-PBA at a dose of 0.5 mg·g~(-1), and the control and model groups were given an equal volume of carboxylmethyl cellulose sodium. The treatments were administered once daily for 8 weeks. Food intake, water consumption, and body weight were recorded every 2 weeks. After the intervention, fasting blood glucose(FBG), glycosylated hemoglobin(HbA1c), urine microalbumin(U-mALB), 24-hour urine volume, serum creatinine(Scr), and blood urea nitrogen(BUN) were measured. Inflammatory markers interleukin-1β(IL-1β) and interleukin-18(IL-18) were detected using the enzyme-linked immunosorbent assay(ELISA). Renal pathology was assessed through hematoxylin-eosin(HE), periodic acid-Schiff(PAS), and Masson staining, and transmission electron microscopy(TEM). Western blot was used to detect the expression levels of glucose-regulated protein 78(GRP78), C/EBP homologous protein(CHOP), NLRP3, apoptosis-associated speck-like protein containing CARD(ASC), cysteinyl aspartate-specific proteinase(caspase-1), and gasdermin D(GSDMD) in kidney tissues. The results showed that compared to the control group, the model group exhibited poor general condition, increased weight and food and water intake, and significantly higher levels of FBG, HbA1c, U-mALB, kidney index, 24-hour urine volume, IL-1β, and IL-18. Compared to the model group, the YSJTD and 4-PBA groups showed improved general condition, increased body weight, decreased food intake, and lower levels of FBG, U-mALB, kidney index, 24-hour urine volume, and IL-1β. Specifically, the YSJTD group showed a significant reduction in IL-18 levels compared to the model group, while the 4-PBA group exhibited decreased water intake and HbA1c levels compared to the model group. Although there was a decreasing trend in water intake and HbA1c in the YSJTD group, the differences were not statistically significant. No significant differences were observed in BUN, Scr, and kidney weight among the groups. Renal pathology revealed that the model group exhibited more severe renal damage compared to the control group. Kidney sections from the model group showed diffuse mesangial proliferation in the glomeruli, tubular edema, tubular dilation, significant inflammatory cell infiltration in the interstitium, and increased glycogen staining and blue collagen deposition in the basement membrane. In contrast, the YSJTD and 4-PBA groups showed varying degrees of improvement in renal damage, glycogen staining, and collagen deposition, with the YSJTD group showing more significant improvements. TEM analysis indicated that the model group had extensive cytoplasmic edema, homogeneous thickening of the basement membrane, fewer foot processes, and widening of fused foot processes. In the YSJTD and 4-PBA groups, cytoplasmic swelling of renal tissues was reduced, the basement membrane remained intact and uniform, and foot process fusion improved.Western blot results indicated that compared to the control group, the model group showed upregulation of GRP78, CHOP, GSDMD, NLRP3, ASC, and caspase-1 expression. In contrast, both the YSJTD and 4-PBA groups showed downregulation of these markers compared to the model group. These findings suggest that YSJTD exerts a protective effect against DN by alleviating NLRP3 inflammasome activation through the inhibition of ERS, thereby improving the inflammatory response in db/db DN mice.

PMID:40686143 | DOI:10.19540/j.cnki.cjcmm.20250114.401

Zhongguo Zhong Yao Za Zhi. 2025 May;50(10):2684-2694. doi: 10.19540/j.cnki.cjcmm.20250207.301.

ABSTRACT

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.

PMID:40686137 | DOI:10.19540/j.cnki.cjcmm.20250207.301

Knee Surg Sports Traumatol Arthrosc. 2025 Jul 21. doi: 10.1002/ksa.12757. Online ahead of print.

ABSTRACT

PURPOSE: Determine whether patellar height differs significantly between knees with objective patellar instability (OPI) and controls, and to develop a magnetic resonance imaging-based (MRI-based) quantitative method for classifying ‘functional patella alta’ relative to both tibia and trochlea.

METHODS: This cross-sectional study included all records of adults who underwent an MRI of their knee between 2019 and 2022 at the senior authors’ centre. The OPI group (n = 127) included patients with >2 documented episodes of lateral patellar dislocation and no previous knee surgery, and the control group (n = 97) included patients with isolated meniscal tears and no history of patellofemoral disorders or knee surgery. Four readers independently measured the MRI patellar height index (PHI), the sagittal patellar engagement (SPE) index and the patellar tendon length (PTL). The control group’s interquartile ranges of PHI (75th percentile) and SPE index (25th percentile) were used to define ‘patella norma’ (PHI ≤ 1.16 and SPE index ≥ 0.38) and ‘functional patella alta’ (PHI > 1.16 and SPE index < 0.38). Multivariable logistic regression analyses assessed the associations between patellar height and trochlear dysplasia with knees exhibiting OPI.

RESULTS: Comparison between ‘patella norma’ and ‘functional patella alta’ revealed statistically significant differences for PHI (mean difference [MD], -0.23; p < 0.001), SPE index (MD, 0.28; p < 0.001) and PTL (MD, -7; p < 0.001). The prevalence of ‘functional patella alta’ was 24% in OPI knees (30 of 127) and 6% in control knees (6 of 97). Multivariable logistic regression revealed that ‘functional patella alta’ and trochlear dysplasia were independently associated with OPI.

CONCLUSION: Standardized MRI-based assessment of patella alta relative to both tibia and trochlea is reliable using thresholds of PHI (>1.16) and SPE index (<0.38). These thresholds, specifically developed for MRI, should improve the conventional assessment using the Caton-Deschamps index, originally developed for true lateral radiographs.

LEVEL OF EVIDENCE: Level III.

PMID:40686068 | DOI:10.1002/ksa.12757

Analyst. 2025 Jul 21. doi: 10.1039/d5an00521c. Online ahead of print.

ABSTRACT

Detection and discrimination of neonicotinoid insecticides (NNIs) are highly desired, but they are still challenging tasks owing to the minor differences in the molecular structures among the massive subtypes of NNIs. In this work, a room-temperature phosphorescence (RTP) sensor array for the detection and discrimination of NNIs was fabricated via a host-guest doping strategy. NNIs were doped into a boric acid host, which enhanced its RTP intensities by inhibiting the molecular motion, narrowing the energy gap between the singlet and triplet states, and providing rigid protection structures. A sensor array was fabricated by integrating the RTP intensities and emission lifetimes. Five types of NNIs were quantitatively detected and discriminated using statistical algorithms. Aided by the delayed collection model of the RTP signal, the sensor array showed excellent detection performance in real food samples. These results open a new door for designing various detection routes for applications in food analysis.

PMID:40686059 | DOI:10.1039/d5an00521c

Disaster Med Public Health Prep. 2025 Jul 21;19:e198. doi: 10.1017/dmp.2025.10124.

ABSTRACT

Anesthesiologists are broadly trained members of the health care workforce, managing patients daily using advanced stabilization/resuscitative techniques. They work in a collaborative, team-based model and lead multidisciplinary teams. Their work includes prioritizing patients according to the complexities of their disease presentations, and threats to life and limb. Trauma care is a regular part of the anesthesiologist’s job. The presence of anesthesiologists is required in hospitals to achieve the designation “level 1” trauma center. Anesthesiology is a specialty known for promoting safe practice principles and improving quality of care, utilizing crisis resource management and implementing cognitive aids. Despite these skillsets, anesthesiologists are generally overlooked in disaster preparedness. The number of trained anesthesiologists is similar to that of emergency medicine physicians, and they are nearly twice as abundant as general surgeons. In countries outside the US, anesthesiologists are often included in the pre-hospital team.The purpose of this article is to emphasize the skillsets of anesthesiologists and to advocate for their inclusion in disaster preparedness teams. Due to their presence and comfort throughout the hospital system, broad training in emergent and elective cases, resuscitation skills, procedural skills, communication skills, daily triage, and team management, anesthesiologists should be considered essential leaders during mass casualty incident preparation and response.

PMID:40686050 | DOI:10.1017/dmp.2025.10124

Disaster Med Public Health Prep. 2025 Jul 21;19:e196. doi: 10.1017/dmp.2025.10071.

ABSTRACT

OBJECTIVES: The objective of this scoping review is to identify the types of EMC provided by humanitarian organizations in response to sudden-onset disasters in Southeast Asia in the last 10 years.

METHODS: We followed Arskey and O’Malley method and Joanna Briggs Institute guidance. Limited to online-based journal databases (PubMed, Embase, and ProQuest) and ReliefWeb and PreventionWeb for grey literature between 2014 and 2023. Study was performed from January-June 2024.

RESULTS: Finally, 33 studies were included covering 17 disasters (Indonesia, Philippines, Laos, and Myanmar). Fourteen disasters were caused by a single hazard: earthquakes (6, 35.3%), floods (4, 23,5%), cyclones (2, 11.8%), tsunamis (1, 5.9%), and volcanic eruptions, and 3 were multi-hazard: earthquakes and tsunamis (2, 11.8%) and flood and landslide (1, 5.9%). The main services provided were mental health and psychosocial support; assessment, resuscitation, and stabilization; referral and transfer; and health promotion and community engagement.

CONCLUSIONS: Humanitarian organizations should prioritize services to meet demands: mental health and psychosocial support; assessment, resuscitation, and stabilization; referral and transfer; and health promotion and community engagement. This can guide national governments in scaling up preparedness and response efforts, ensuring that demands are met at a local level but also aligned with international disaster response.

PMID:40686046 | DOI:10.1017/dmp.2025.10071

Disaster Med Public Health Prep. 2025 Jul 21;19:e197. doi: 10.1017/dmp.2025.10062.

ABSTRACT

OBJECTIVES: Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding the dynamics of epidemic spread during warfare is essential for developing effective containment strategies in complex conflict zones. While research has explored epidemic models in various settings, the impact of warfare on epidemic dynamics remains underexplored.

METHODS: We proposed a novel mathematical model that integrates the epidemiological SIR (susceptible-infected-recovered) model with the war dynamics Lanchester model to explore the dual influence of war and pandemic on a population’s mortality. Moreover, we consider a dual-use military and civil health care system that aims to reduce the overall mortality rate, which can use different administration policies such as prioritizing soldiers over civilians. Using an agent-based simulation to generate in silico data, we trained a deep reinforcement learning model based on the deep Q-network algorithm for health care administration policy and conducted an intensive investigation on its performance.

RESULTS: Our results show that a pandemic during war conduces chaotic dynamics where the health care system should either prioritize war-injured soldiers or pandemic-infected civilians based on the immediate amount of mortality from each option, ignoring long-term objectives.

CONCLUSIONS: Our findings highlight the importance of integrating conflict-related factors into epidemic modeling to enhance preparedness and response strategies in conflict-affected areas.

PMID:40686043 | DOI:10.1017/dmp.2025.10062

Br J Psychiatry. 2025 Jul 21:1-2. doi: 10.1192/bjp.2025.113. Online ahead of print.

NO ABSTRACT

PMID:40686042 | DOI:10.1192/bjp.2025.113

J Dairy Res. 2025 Jul 21:1-5. doi: 10.1017/S0022029925100976. Online ahead of print.

ABSTRACT

To understand the requirements of animals their calls can be analysed. This potentially enables specific and more precise individual care under different emotional and physiological conditions. This study was conducted to identify three different conditions (oestrus, delayed milking and isolation) of buffaloes based on vocalization patterns. A total of 600 acoustic samples of buffaloes for each condition were collected under different conditions consisting of 300 records for confirming and 300 for non-confirming of a particular condition. Important acoustic features like amplitude (P), total energy (P²s), pitch (Hz), intensity (dB), formants (Hz), number of pulses, number of periods, mean period (sec) and unvoiced frames (%) were extracted using the MFCC (mel frequency cepstrum coefficients) technique. Algorithms (model) were trained by partitioning the acoustic data into training and validation sets to develop predictive models. Three different ratios were assessed: 60%-40%, 70%-30% and 80%-20%. Decision tree models were optimized based on decision and average square error (probability) options and other parameters were set to default values of the software package to deveop the best model. The performance of algorithms was evaluated on the parameter accuracy rate. Decision tree models predicted the physiological conditions oestrus, isolation and delayed milking with an accuracy of 66.1, 84.3 and 71.3%, respectively, while the logistic regression model predicted with an accuracy rate of 59.5, 71.1 and 65.7%, respectively, and the artificial neural network (ANN) model predicted these three conditions with 77.7, 85.2 and 79.4% accuracy, respectively. The ANN model was found to be best on the basis of minimum misclassification rate (on 80%-20% portioning). However, decision tree algorithms also provided the additional information that intensity (maximum), amplitude (minimum) and formant (F1) are the most important features of vocal signals to identify physiological conditions like oestrus, isolation and delayed milking respectively in dairy buffalo.

PMID:40686040 | DOI:10.1017/S0022029925100976