UNASSIGNED: Antidepressants still have some side effects in treating major depressive disorder (MDD), and acupuncture therapy is a complementary therapy of research interest for MDD. Acupoints are sensitive sites for disease response and stimulation points for acupuncture treatment. Prior studies suggest that the biological specificity of acupoints is altered in physiological and pathological situations. Therefore, we hypothesize that the biological specificity of acupoints is associated with the diagnosis of MDD and that stimulating acupoints with significant biological specificity can achieve a better therapeutic effect than clinical common acupoints. This study aims to investigate the efficacy and safety of intradermal acupuncture (IA) treatment for MDD based on changes in the biological specificity of acupoints.
UNASSIGNED: The first part of the study will enroll 30 MDD patients and 30 healthy control (HC) participants to assess pain sensitivity and thermal specificity of MDD-related acupoints using a pressure pain threshold gauge (PTG) and infrared thermography (IRT). The potentially superior acupoints for treating MDD will be selected based on the results of PTG and IRT tests and referred to as pressure pain threshold strong response acupoints (PSA) and temperature strong response acupoints (TSA).The second part of the study will enroll 120 eligible MDD patients randomly assigned to waiting list (WL) group, clinical common acupoint (CCA) group, TSA group, and PSA group in a 1:1:1:1 ratio. The change in the Patient Health Questionnaire-9 Items (PHQ-9), the MOS item short-form health survey (SF-36), pressure pain threshold, temperature of acupoints, and adverse effects will be observed. The outcomes of PHQ-9 and SF-36 measures will be assessed before intervention, at 3 and 6 weeks after intervention, and at a 4-week follow-up. The biological specificity of acupoint measures will be assessed before intervention and at 6 weeks after intervention. All adverse effects will be assessed.
UNASSIGNED: This study will evaluate the therapeutic effect and safety of IA for MDD based on changes in the biological specificity of acupoints. It will investigate whether there is a correlation between the biological specificity of MDD-related acupoints and the diagnosis of MDD and whether stimulating strong response acupoints is superior to clinical common acupoints in the treatment of MDD. The study\'s results may provide insights into the biological mechanisms of acupuncture and its potential as a complementary therapy for MDD.
UNASSIGNED: ClinicalTrials.gov, identifier: NCT05524519.

Human plasminogen Kringle 5 is known to pose a more potent anti-angiogenesis effect by inducing endothelial cell apoptosis. Our previous studies have identified the peptide IGNSNTL as a binding sequence of Kringle 5 using Ph.D.-7 phage display peptide library and enzyme-linked immunosorbent assay. Here, eleven proteins were screened and summarized by BLAST, laminin α3 chain G1 domain (LG1) was considered as the most potential receptor based on E value and domain function. The specific interaction of them was directly revealed through ligand blot and a strong concentration-dependent manner occurred between them (Ka 4.30 × 105 L mol-1) in frontal chromatography observation. Moreover, R10A/P83R substitution Kringle 5 decreased the affinity capacity to LG1. Furthermore, a remarkable conformational change from random coil3 to α helix and α1 helix to random coil were observed to the structural compactness and stability for LG1. Surface loops and coils also showed fluctuations up to some extent, giving the binding surface greater flexibility and correspondingly allowing for induced-fit binding, which was -23.87 kcal mol-1 of the free energy with electrostatic force as a main driver. Taken together, not only effective theoretical prediction and experiment validated that LG1 is receptor of Kringle 5, but also give an new perspective of the binding mechanism of Kringle 5 and its specific receptor and could facilitate the development of novel agent targeted toward pathologic angiogenesis.

The experimental evidence has shown that the genetic code is based on arbitrary, or conventional, rules, in the sense that any codon can be associated to any amino acid, and this means that there is no deterministic link between them. This is in sharp contrast with the traditional paradigm of the stereochemical theory, which claims that the rules of the genetic code were determined by chemistry, and more precisely by stereochemical affinities between codons and amino acids. The discovery that the genetic code is based on arbitrary rules, on the other hand, raised a formidable problem: how can such rules exist in Nature? In order to deal with this problem, it has been pointed out that the rules of an arbitrary code could not come fully formed into existence. The first genetic code, in other words, was necessarily ambiguous, and its evolution took place with a mechanism that systematically reduced its ambiguity and eventually removed it. The concept of ambiguity-reduction has been repeatedly mentioned in the scientific literature, but very few papers have actually addressed the problem of its mechanism. One of these papers was published with the name of ribosome-oriented model in order to underline the key role that the ribosomal proteins had in that process, but later on it became clear that other factors had to be taken into account. This is why the ribosome-oriented model had to be extended and here a more general version is proposed with the name of ambiguity-reduction theory.

Biology arises from the crowded molecular environment of the cell, rendering it a challenge to understand biological pathways based on the reductionist, low-concentration in vitro conditions generally employed for mechanistic studies. Recent evidence suggests that low-affinity interactions between cellular biopolymers abound, with still poorly defined effects on the complex interaction networks that lead to the emergent properties and plasticity of life. Mass-action considerations are used here to underscore that the sheer number of weak interactions expected from the complex mixture of cellular components significantly shapes biological pathway specificity. In particular, on-pathway-i.e., \"functional\"-become those interactions thermodynamically and kinetically stable enough to survive the incessant onslaught of the many off-pathway (\"nonfunctional\") interactions. Consequently, to better understand the molecular biology of the cell a further paradigm shift is needed toward mechanistic experimental and computational approaches that probe intracellular diversity and complexity more directly. Also see the video abstract here https://youtu.be/T19X_zYaBzg.

Mathematical models have been widespread in biology since its emergence as a modern experimental science in the 19th century. Focusing on models in developmental biology and heredity, this article (1) presents the properties and epistemological basis of pertinent mathematical models in biology from Mendel\'s model of heredity in the 19th century to Eric Davidson\'s model of developmental gene regulatory networks in the 21st; (2) shows that the models differ not only in their epistemologies but also in regard to explicitly or implicitly taking into account basic biological principles, in particular those of biological specificity (that became, in part, replaced by genetic information) and genetic causality. The article claims that models disregarding these principles did not impact the direction of biological research in a lasting way, although some of them, such as D\'Arcy Thompson\'s models of biological form, were widely read and admired and others, such as Turing\'s models of development, stimulated research in other fields. Moreover, it suggests that successful models were not purely mathematical descriptions or simulations of biological phenomena but were based on inductive, as well as hypothetico-deductive, methodology. The recent availability of large amounts of sequencing data and new computational methodology tremendously facilitates system approaches and pattern recognition in many fields of research. Although these new technologies have given rise to claims that correlation is replacing experimentation and causal analysis, the article argues that the inductive and hypothetico-deductive experimental methodologies have remained fundamentally important as long as causal-mechanistic explanations of complex systems are pursued.